| --- |
| tags: autotrain |
| language: en |
| widget: |
| - text: "Why is the username the largest part of each card?" |
| datasets: |
| - Shenzy2/autotrain-data-NER4DesignTutor |
| co2_eq_emissions: 0.004032656988228696 |
| --- |
| |
| # Model Trained Using AutoTrain |
|
|
| - Problem type: Entity Extraction |
| - Model ID: 1169643336 |
| - CO2 Emissions (in grams): 0.004032656988228696 |
|
|
| ## Validation Metrics |
|
|
| - Loss: 0.677674412727356 |
| - Accuracy: 0.8129095674967235 |
| - Precision: 0.4424778761061947 |
| - Recall: 0.4844961240310077 |
| - F1: 0.4625346901017577 |
|
|
| ## Usage |
|
|
| You can use cURL to access this model: |
|
|
| ``` |
| $ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "Why is the username the largest part of each card?"}' https://api-inference.huggingface.co/models/Shenzy2/NER4DesignTutor |
| ``` |
|
|
| Or Python API: |
|
|
| ``` |
| from transformers import AutoModelForTokenClassification, AutoTokenizer |
| |
| model = AutoModelForTokenClassification.from_pretrained("Shenzy2/NER4DesignTutor") |
| |
| tokenizer = AutoTokenizer.from_pretrained("Shenzy2/NER4DesignTutor") |
| |
| inputs = tokenizer("Why is the username the largest part of each card?", return_tensors="pt") |
| |
| outputs = model(**inputs) |
| ``` |
